Adaptive nonlocal means-based regularization for statistical image reconstruction of low-dose X-ray CT

Hao Zhang, Jianhua Ma, Jing Wang, Yan Liu, Hao Han, Lihong Li, William Moore, Zhengrong Liang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

To reduce radiation dose in X-ray computed tomography (CT) imaging, one of the common strategies is to lower the milliampere-second (mAs) setting during projection data acquisition. However, this strategy would inevitably increase the projection data noise, and the resulting image by the filtered back-projection (FBP) method may suffer from excessive noise and streak artifacts. The edge-preserving nonlocal means (NLM) filtering can help to reduce the noise-induced artifacts in the FBP reconstructed image, but it sometimes cannot completely eliminate them, especially under very low-dose circumstance when the image is severely degraded. To deal with this situation, we proposed a statistical image reconstruction scheme using a NLM-based regularization, which can suppress the noise and streak artifacts more effectively. However, we noticed that using uniform filtering parameter in the NLM-based regularization was rarely optimal for the entire image. Therefore, in this study, we further developed a novel approach for designing adaptive filtering parameters by considering local characteristics of the image, and the resulting regularization is referred to as adaptive NLM-based regularization. Experimental results with physical phantom and clinical patient data validated the superiority of using the proposed adaptive NLM-regularized statistical image reconstruction method for low-dose X-ray CT, in terms of noise/streak artifacts suppression and edge/detail/contrast/texture preservation.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2015: Physics of Medical Imaging
PublisherSPIE
Volume9412
ISBN (Electronic)9781628415025
DOIs
StatePublished - 2015
EventMedical Imaging 2015: Physics of Medical Imaging - Orlando, United States
Duration: Feb 22 2015Feb 25 2015

Other

OtherMedical Imaging 2015: Physics of Medical Imaging
CountryUnited States
CityOrlando
Period2/22/152/25/15

Fingerprint

X Ray Computed Tomography
Computer-Assisted Image Processing
image reconstruction
Image reconstruction
Dosimetry
Tomography
Noise
tomography
Artifacts
artifacts
X rays
dosage
projection
Adaptive filtering
Data acquisition
x rays
Textures
Imaging techniques
preserving
data acquisition

Keywords

  • Adaptive nonlocal means
  • Low-dose
  • Penalized weighted least-squares
  • Regularization
  • Statistical image reconstruction
  • X-ray CT

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Radiology Nuclear Medicine and imaging

Cite this

Zhang, H., Ma, J., Wang, J., Liu, Y., Han, H., Li, L., ... Liang, Z. (2015). Adaptive nonlocal means-based regularization for statistical image reconstruction of low-dose X-ray CT. In Medical Imaging 2015: Physics of Medical Imaging (Vol. 9412). [94123K] SPIE. https://doi.org/10.1117/12.2082244

Adaptive nonlocal means-based regularization for statistical image reconstruction of low-dose X-ray CT. / Zhang, Hao; Ma, Jianhua; Wang, Jing; Liu, Yan; Han, Hao; Li, Lihong; Moore, William; Liang, Zhengrong.

Medical Imaging 2015: Physics of Medical Imaging. Vol. 9412 SPIE, 2015. 94123K.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zhang, H, Ma, J, Wang, J, Liu, Y, Han, H, Li, L, Moore, W & Liang, Z 2015, Adaptive nonlocal means-based regularization for statistical image reconstruction of low-dose X-ray CT. in Medical Imaging 2015: Physics of Medical Imaging. vol. 9412, 94123K, SPIE, Medical Imaging 2015: Physics of Medical Imaging, Orlando, United States, 2/22/15. https://doi.org/10.1117/12.2082244
Zhang H, Ma J, Wang J, Liu Y, Han H, Li L et al. Adaptive nonlocal means-based regularization for statistical image reconstruction of low-dose X-ray CT. In Medical Imaging 2015: Physics of Medical Imaging. Vol. 9412. SPIE. 2015. 94123K https://doi.org/10.1117/12.2082244
Zhang, Hao ; Ma, Jianhua ; Wang, Jing ; Liu, Yan ; Han, Hao ; Li, Lihong ; Moore, William ; Liang, Zhengrong. / Adaptive nonlocal means-based regularization for statistical image reconstruction of low-dose X-ray CT. Medical Imaging 2015: Physics of Medical Imaging. Vol. 9412 SPIE, 2015.
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